Spatial-explicit modeling of social vulnerability to malaria in East AfricaReport as inadecuate

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International Journal of Health Geographics

, 13:29

First Online: 15 August 2014Received: 23 May 2014Accepted: 06 August 2014DOI: 10.1186-1476-072X-13-29

Cite this article as: Kienberger, S. & Hagenlocher, M. Int J Health Geogr 2014 13: 29. doi:10.1186-1476-072X-13-29


BackgroundDespite efforts in eradication and control, malaria remains a global challenge, particularly affecting vulnerable groups. Despite the recession in malaria cases, previously malaria free areas are increasingly confronted with epidemics as a result of changing environmental and socioeconomic conditions. Next to modeling transmission intensities and probabilities, integrated spatial methods targeting the complex interplay of factors that contribute to social vulnerability are required to effectively reduce malaria burden. We propose an integrative method for mapping relative levels of social vulnerability in a spatially explicit manner to support the identification of intervention measures.

MethodsBased on a literature review, a holistic risk and vulnerability framework has been developed to guide the assessment of social vulnerability to water-related vector-borne diseases VBDs in the context of changing environmental and societal conditions. Building on the framework, this paper applies spatially explicit modeling for delineating homogeneous regions of social vulnerability to malaria in eastern Africa, while taking into account expert knowledge for weighting the single vulnerability indicators. To assess the influence of the selected indicators on the final index a local sensitivity analysis is carried out.

ResultsResults indicate that high levels of malaria vulnerability are concentrated in the highlands, where immunity within the population is currently low. Additionally, regions with a lack of access to education and health services aggravate vulnerability. Lower values can be found in regions with relatively low poverty, low population pressure, low conflict density and reduced contributions from the biological susceptibility domain. Overall, the factors characterizing vulnerability vary spatially in the region. The vulnerability index reveals a high level of robustness in regard to the final choice of input datasets, with the exception of the immunity indicator which has a marked impact on the composite vulnerability index.

ConclusionsWe introduce a conceptual framework for modeling risk and vulnerability to VBDs. Drawing on the framework we modeled social vulnerability to malaria in the context of global change using a spatially explicit approach. The results provide decision makers with place-specific options for targeting interventions that aim at reducing the burden of the disease amongst the different vulnerable population groups.

KeywordsMalaria Vulnerability Climate change adaptation Integrated spatial modeling Geon concept Regionalization Eastern Africa Electronic supplementary materialThe online version of this article doi:10.1186-1476-072X-13-29 contains supplementary material, which is available to authorized users.

Stefan Kienberger and Michael Hagenlocher contributed equally to this work.

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Author: Stefan Kienberger - Michael Hagenlocher


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